Explore MATLAB source code curated for "中心" with clean implementations, documentation, and examples.
This program focuses on measuring object perimeter and detecting center points in digital image processing, with additional functionality for drawing minimum bounding rectangles around detected objects. It implements key computer vision algorithms including edge detection, thresholding, morphological operations, and image segmentation techniques.
Generate a Gaussian amplitude-modulated signal centered at time t0 using AMGAUSS function. N specifies the number of signal points, t0 defines the temporal center, and y returns the generated signal. The implementation uses Gaussian windowing combined with amplitude modulation to create signals with optimized spectral properties.
Determining the center of a light spot image using the centroid method by calculating the ratio of the sum of each pixel's grayscale value multiplied by its position to the total grayscale value sum
Familiarize with concepts of triangular fuzzy numbers, centers, and membership function expressions. Learn about feature mapping algorithms and statistical metric concepts. Implement cluster iteration algorithms to construct triangular-shaped membership functions with proper parameter initialization and convergence criteria.
RBF networks face challenges in determining hidden layer node centers and basis width parameters; they possess unique optimal approximation properties without local minima. However, their Gaussian activation functions exhibit localized characteristics. We implement function approximation using fuzzy RBF networks, which effectively handle fuzzy data and uncertainty through integrated membership functions and rule-based reasoning mechanisms.
Method for calculating the center coordinates of grayscale spot images, applicable to various spot types including laser spots, with implementation approaches using centroid calculation and Gaussian fitting algorithms